Suspect Screening and Prioritization as an Analytical Strategy for the Identification of Persistent, Mobile, and Toxic (PMT) Substances in Surface Water

High Resolution Image Download MS PowerPoint Slide Persistent, mobile, and toxic (PMT) substances have gained increasing scientific and regulatory attention due to their capacity to bypass natural and artificial barriers and spread throughout the water cycle. However, knowledge of their environmental occurrence remains limited due to analytical challenges, particularly in detecting highly polar substances that are often overlooked in monitoring studies. This study aims to identify PMT substances that are worth monitoring in surface waters strongly influenced by wastewater treatment plant effluents. A suspect screening analysis (SSA) approach based on the use of LC-HRMS was integrated with a tiered prioritization strategy. Our workflow integrates multimodal SPE and LC approaches to improve PMT detection coverage across polarity gradients. A total of 305 substances were tentatively identified, and 103 of them were prioritized as PMT substances, encompassing industrial chemicals, personal care products, pharmaceuticals, illicit drugs, pesticides, and transformation products. Notably, only 13% of PMT substances are currently included in the European Water Framework Directive legislation or the REACH list of substances of very high concern. Among them, 35 high-priority PMT substances were confirmed with analytical standards through mass spectrometry (MS/MS) in tandem with HRMS, providing reliable fragmentation data. Some of these substances such as the pharmaceutical celecoxib, the ultrashort-chain per- and polyfluoroalkyl substance (PFAS) bis(trifluoromethylsulfonyl)imide, or the industrial chemical 1,3-di- o -tolylguanidine (DTG) have been scarcely investigated in environmental monitoring efforts. The methodological framework presented in this study is readily adaptable to a wide range of environmental scenarios. The results obtained highlight the importance of integrating SSA as a complementary approach to conventional target analysis.